FMRI-based identity classification accuracy in left temporal and frontal regions predicts speaker recognition performance

Abstract Speaker recognition is characterized by considerable inter-individual variability with poorly understood neural bases. This study was aimed at (1) clarifying the cerebral correlates of speaker recognition in humans, in particular the involvement of prefrontal areas, using multi voxel patter...

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Autores principales:	Virginia Aglieri, Bastien Cagna, Lionel Velly, Sylvain Takerkart, Pascal Belin
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/a0a17f0cc1d142df864513649eab5736
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spelling	oai:doaj.org-article:a0a17f0cc1d142df864513649eab57362021-12-02T15:23:06ZFMRI-based identity classification accuracy in left temporal and frontal regions predicts speaker recognition performance10.1038/s41598-020-79922-72045-2322https://doaj.org/article/a0a17f0cc1d142df864513649eab57362021-01-01T00:00:00Zhttps://doi.org/10.1038/s41598-020-79922-7https://doaj.org/toc/2045-2322Abstract Speaker recognition is characterized by considerable inter-individual variability with poorly understood neural bases. This study was aimed at (1) clarifying the cerebral correlates of speaker recognition in humans, in particular the involvement of prefrontal areas, using multi voxel pattern analysis (MVPA) applied to fMRI data from a relatively large group of participants, and (2) at investigating the relationship across participants between fMRI-based classification and the group’s variable behavioural performance at the speaker recognition task. A cohort of subjects (N = 40, 28 females) selected to present a wide distribution of voice recognition abilities underwent an fMRI speaker identification task during which they were asked to recognize three previously learned speakers with finger button presses. The results showed that speaker identity could be significantly decoded based on fMRI patterns in voice-sensitive regions including bilateral temporal voice areas (TVAs) along the superior temporal sulcus/gyrus but also in bilateral parietal and left inferior frontal regions. Furthermore, fMRI-based classification accuracy showed a significant correlation with individual behavioural performance in left anterior STG/STS and left inferior frontal gyrus. These results highlight the role of both temporal and extra-temporal regions in performing a speaker identity recognition task with motor responses.Virginia AglieriBastien CagnaLionel VellySylvain TakerkartPascal BelinNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-13 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Virginia Aglieri Bastien Cagna Lionel Velly Sylvain Takerkart Pascal Belin FMRI-based identity classification accuracy in left temporal and frontal regions predicts speaker recognition performance
description	Abstract Speaker recognition is characterized by considerable inter-individual variability with poorly understood neural bases. This study was aimed at (1) clarifying the cerebral correlates of speaker recognition in humans, in particular the involvement of prefrontal areas, using multi voxel pattern analysis (MVPA) applied to fMRI data from a relatively large group of participants, and (2) at investigating the relationship across participants between fMRI-based classification and the group’s variable behavioural performance at the speaker recognition task. A cohort of subjects (N = 40, 28 females) selected to present a wide distribution of voice recognition abilities underwent an fMRI speaker identification task during which they were asked to recognize three previously learned speakers with finger button presses. The results showed that speaker identity could be significantly decoded based on fMRI patterns in voice-sensitive regions including bilateral temporal voice areas (TVAs) along the superior temporal sulcus/gyrus but also in bilateral parietal and left inferior frontal regions. Furthermore, fMRI-based classification accuracy showed a significant correlation with individual behavioural performance in left anterior STG/STS and left inferior frontal gyrus. These results highlight the role of both temporal and extra-temporal regions in performing a speaker identity recognition task with motor responses.
format	article
author	Virginia Aglieri Bastien Cagna Lionel Velly Sylvain Takerkart Pascal Belin
author_facet	Virginia Aglieri Bastien Cagna Lionel Velly Sylvain Takerkart Pascal Belin
author_sort	Virginia Aglieri
title	FMRI-based identity classification accuracy in left temporal and frontal regions predicts speaker recognition performance
title_short	FMRI-based identity classification accuracy in left temporal and frontal regions predicts speaker recognition performance
title_full	FMRI-based identity classification accuracy in left temporal and frontal regions predicts speaker recognition performance
title_fullStr	FMRI-based identity classification accuracy in left temporal and frontal regions predicts speaker recognition performance
title_full_unstemmed	FMRI-based identity classification accuracy in left temporal and frontal regions predicts speaker recognition performance
title_sort	fmri-based identity classification accuracy in left temporal and frontal regions predicts speaker recognition performance
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/a0a17f0cc1d142df864513649eab5736
work_keys_str_mv	AT virginiaaglieri fmribasedidentityclassificationaccuracyinlefttemporalandfrontalregionspredictsspeakerrecognitionperformance AT bastiencagna fmribasedidentityclassificationaccuracyinlefttemporalandfrontalregionspredictsspeakerrecognitionperformance AT lionelvelly fmribasedidentityclassificationaccuracyinlefttemporalandfrontalregionspredictsspeakerrecognitionperformance AT sylvaintakerkart fmribasedidentityclassificationaccuracyinlefttemporalandfrontalregionspredictsspeakerrecognitionperformance AT pascalbelin fmribasedidentityclassificationaccuracyinlefttemporalandfrontalregionspredictsspeakerrecognitionperformance
_version_	1718387343289745408

FMRI-based identity classification accuracy in left temporal and frontal regions predicts speaker recognition performance

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